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Record W4308387372

Nepal Health Research Council Paves Path to Ethical Research Processes

2018· article· en· W4308387372 on OpenAlex
Sunisha Neupane, Chaitali Sinha

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2018
Typearticle
Languageen
FieldMedicine
TopicScience, Research, and Medicine
Canadian institutionsInternational Development Research CentreUniversité de Montréal
Fundersnot available
KeywordsPath (computing)Engineering ethicsPolitical scienceResearch ethicsSociologyManagement scienceComputer scienceEngineering
DOInot available

Abstract

fetched live from OpenAlex

This case study outlines an ethics approval process experienced during a maternal health research project in Nepal. The Government of Nepal established the Nepal Health Research Council (NHRC) in 1991, along with the Scientific and Ethics Committee reviewing health related research. However, not all researchers apply for ethics approval. Although researchers may claim a lack of clarity on the kinds of research studies needing approval, the authors argue that the guidelines are sufficiently clear if explored and duly followed. The inconsistencies in seeking ethics approval from NHRC could simply mean that researchers are not aware of this ethical review process. Perhaps the guidelines are not strictly enforced. Nevertheless, as researchers it is our responsibility to seek ethical approval as a matter of principle, without considering it a barrier to research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.069
metaresearch head score (Gemma)0.044
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.389
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0690.044
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.009
Science and technology studies0.0020.003
Scholarly communication0.0010.001
Open science0.0040.002
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0090.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.849
GPT teacher head0.730
Teacher spread0.119 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it